Political Instability Task Force
The Political Instability Task Force (PITF), formerly known as State Failure Task Force, is a
Project history
The project began as an unclassified study that was commissioned to a group of
Methodology
The PITF first identified over 100 "problem cases" in the world from 1955 to 2011.
The goal was to find factors associated with major political conflicts.[4] Over 400 cases were analyzed, both for global and regional data sets.[4]
The common variables listed in each data version are as follows:
- COUNTRY - Full alpha country name
- SCODE - 3-letter alpha country code
- CCODE - 3-number numeric Singer country code
- YEAR - 4-number numeric year
- MOBEGIN - 2-number numeric month denoting event beginning
- YRBEGIN - 4-number numeric year denoting event beginning
- MOEND - 2-number numeric month denoting event ending (99=ongoing)
- YREND - 4-number numeric year denoting event ending (9999=ongoing)
- PTYPE - 1-number numeric event type (1=ETH; 2=REV; 3=REG; 4=GEN)
- DESC - Brief alpha text description identifying specific event (only included with first case-year in multi-year episodes)
Revolutionary and Ethnic Wars
Revolutionary wars are episodes of violent conflict between governments and politically organized groups (political challengers) that seek to overthrow the central government, to replace its leaders, or to seize power in one region. Conflicts must include substantial use of violence by one or both parties to qualify as "wars."
Additional variables specific to the Ethnic and Revolutionary War episodes are as follows:
- MAGFIGHT - Scaled number of rebel combatants or activists (range 0–4; 9=missing)
- MAGFATAL - Scaled annual number of fatalities related to fighting (range 0–4; 9=missing)
- MAGAREA - Scaled portion of country affected by fighting (range 0–4; 9=missing)
- AVEMAG - Average of the three magnitude scores (range 0–4.0; 9=missing)
Adverse Regime Change
Adverse Regime Changes are defined by the State Failure Task Force as major, adverse shifts in patterns of governance, including
- major and abrupt shifts away from more open, electoral systems to more closed, authoritarian systems;
- revolutionary changes in political elites and the mode of governance;
- contested dissolution of federated states or secession of a substantial area of a state by extrajudicial means; and
- complete or near-total collapse of central state authority and the ability to govern.
Abrupt transitions from more authoritarian rule to more open, institutionalized governance systems, defined by the State Failure Task Force as "democratic transitions," are not considered state failures in this sense and, thus, are not included.
Additional variables specific to the Adverse Regime Change episodes are as follows:
- MAGFAIL - Scaled failure of state authority (range 1–4; 9=missing)
- MAGCOL - Scaled collapse of democratic institutions (range 1–4; 9=missing)
- MAGVIOL - Scaled violence associated with regime transition (range 1–4; 9=missing)
- MAGAVE - Average of the three magnitude scores (range 1–4.0; 9=missing)
- POLITYX - Type of regime change
Genocides and Politicides
Genocide and politicide are distinguished from state repression and terror. In cases of state terror authorities arrest, persecute or execute a few members of a group in ways designed to terrorize the majority of the group into passivity or acquiescence. In the case of genocide and politicide authorities physically exterminate enough (not necessarily all) members of a target group so that it can no longer pose any conceivable threat to their rule or interests.
Additional variables specific to the Genocide/Politicide episodes are as follows:
- DEATHMAG - Scaled annual number of deaths (range 0–5.0)
Findings
Fairly consistent findings were produced, suggesting that there are three
- U-shaped relationship was found between regime type and political unrest: partial democracies were at high risk, whereas both democracies and autocracies were relatively stable.[4]
- waves of revolutions).[4] Being heavily involved in international trade requires respect for the rule of law and low levels of corruption.[4] Countries that do not participate heavily in international trade likely see groups distorting trade and other economic activity for their benefit, making internal conflicts more likely.[4]
- infant mortality. Lower infant mortality, were generally more stable was also positively associated with stability.[4] This is explained as the infant mortality measures for standard of living; therefore countries with low infant mortality rate have more efficient welfare and justice systems.
Thus partial democracies with low involvement in international trade and with high infant mortality are most prone to revolutions.[4]
Quantitative models developed during the study would have accurately predicted over 85% of major state crises events occurring in 1990–1997.[4] However while the models can predict state crises, they cannot predict their magnitude and eventual outcome.[4]
There are four versions of the Political Instability (State Failure) Problem Set data; each are downloadable from the PITF Problem Set page in Microsoft Excel format.[3] This format was chosen because it is readily importable to most spreadsheet and statistical software applications. The four versions are as follows:
- PITF Ethnic Wars 2004.XLS (76 episodes/719 case-years)
- PITF Revolutionary Wars 2004.XLS (64 episodes/472 case-years)
- PITF Adverse Regimes Changes 2004.XLS (112 episodes/284 case-years)
- PITF GenoPoliticides 2004.XLS (41 episodes/268 case-years)
Ethnic Wars
80 cases; 16 ongoing
Revolutionary Wars
65 cases; 4 ongoing
Adverse Regime Changes
115 cases; 2 ongoing
Genocide/Politicides
41 cases; 1 ongoing
Average magnitude over all years: 2.4
Genocides/politicides occurred most frequently in 1975 and 1978. Frequency of occurrence increased beginning in 1962 until 1980, when frequency dropped slightly. The frequency of genocides/politicides plateaued from 1980 to 1987. In 1988 the world saw a slight increase of genocides/politicides, which then quickly turned into a steady decrease in events through 2011.
An example of a typical event: Uganda, 1980–1986. Average magnitude: 3.3.
References
- ^ elite conflicts
- ^ Author andrewperrin (2017-01-20). "why i resigned from the political instability task force". scatterplot. Retrieved 2017-01-22.
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has generic name (help) - ^ a b c "Political Instability Task Force Homepage". Archived from the original on 2006-12-08. Retrieved 2006-11-27.
- ^ a b c d e f g h i j k l Jack Goldstone, "Towards a Fourth Generation of Revolutionary Theory", Annual Review of Political Science 4, 2001:139–87
External links
- PITF State Failure Dataset
- Social Science Statistics Blog: State Failure
- The crystal ball of chaos, Nature,
Further reading
- Goldstone, JA, Bates, RH., Epstein, DL, Gurr, TR, Lustik, MB, Marshall, MG., Ulfelder, J, and Woodward, M. 'A Global Model for Forecasting Political Instability.' American Journal of Political Science, Vol. 54, No. 1 (January 2010), pp. 190–208
- Ulfelder, Jay, and Michael Lustik. "Modelling Transitions to and from Democracy." Democratisation 14.3 (2007): 351–387.
- A global forecasting model of political instability. Political Instability Task Force, 2005.
- Gurr, Ted Robert, Mark R. Woodward, and Monty G. Marshall. Forecasting Instability: Are Ethnic Wars and Muslim Countries Different?. Political Instability Task Force, 2005.
- Harff, B., 'No Lessons Learned from the Holocaust? Assessing Risks of Genocide and political Mass Murder since 1955,' American Political Science Review, Vol. 97, No. 1 (February 2003), pp. 75–90